code: def call(self, inputs, **kwargs):
      # aux1: N x 512 x 14 x 14, aux2: N x 528 x 14 x 14
      x = self.averagePool(inputs)
      # aux1: N x 512 x 4 x 4, aux2: N x 528 x 4 x 4
      x = self.conv(x)
      # N x 128 x 4 x 4
      x = layers.Flatten()(x)
      x = layers.Dropout(rate=0.5)(x)
      # N x 2048
      x = self.fc1(x)
      x = layers.Dropout(rate=0.5)(x)
      # N x 1024
      x = self.fc2(x)
      # N x num_classes
      x = self.softmax(x)
  
      return x
  
file_path: deep-learning-for-image-processing/tensorflow_classification/Test4_goolenet/model.py
imports: from tensorflow.keras import layers, models, Model, Sequential
label_desc: Use image node_id 2 for calling the InceptionAux obj's underlying member method code with example usage: obj.call(inputs) and returns: x